Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index
Article
Chand, Ravinesh, Nguyen-Huy, Thong, Deo, Ravinesh C., Ghimire, Sujan, Ali, Mumtaz and Ghahramani, Afshin. 2024. "Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index." Water. 16 (11). https://doi.org/10.3390/w16111560
| Article Title | Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index |
|---|---|
| Article Category | Article |
| Authors | Chand, Ravinesh, Nguyen-Huy, Thong, Deo, Ravinesh C., Ghimire, Sujan, Ali, Mumtaz and Ghahramani, Afshin |
| Journal Title | Water |
| Journal Citation | 16 (11) |
| Article Number | 1560 |
| Number of Pages | 27 |
| Year | 2024 |
| Publisher | MDPI AG |
| Place of Publication | Switzerland |
| ISSN | 2073-4441 |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/w16111560 |
| Web Address (URL) | https://www.mdpi.com/2073-4441/16/11/1560 |
| Abstract | Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak, and accumulated rainfall-based damage is likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index (πππ πΌ24ββπβπ) derived from normalising the existing 24-hourly water resources index (ππ πΌ24ββπβπ) in the literature to monitor flood risk on an hourly scale. The proposed πππ πΌ24ββπβπ is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V), and peak (Q). The comprehensive result analysis establishes the practical utility of πππ πΌ24ββπβπ in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fijiβs study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak, and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data are available, offering crucial information for flood risk monitoring and assessment and for the development of effective mitigation strategies. |
| Keywords | flood characteristics; vine copulas; risk mitigation; joint distribution; flood monitoring; hourly flood index |
| Related Output | |
| Is part of | Artificial Intelligence and Copula-Probabilistic Models for Early Flood Warning and Community Risk Management: Case Studies in Fiji Islands |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 460207. Modelling and simulation |
| Public Notes | This article is part of a UniSQ Thesis by publication. See Related Output. |
| Byline Affiliations | School of Mathematics, Physics and Computing |
| Centre for Applied Climate Sciences | |
| Thanh Do University, Vietnam | |
| Al-Ayen University, Iraq | |
| UniSQ College | |
| University of Southern Queensland |
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Nguyen, Nguyet-Minh, Bahramloo, Reza, Sadeghian, Jalal, Sepehri, Mehdi, Nazaripouya, Hadi, Dinh, Vuong Nguyen, Ghahramani, Afshin, Talebi, Ali, ElKhrachy, Ismail, Pande, Chaitanya B. and Meshram, Sarita Gajbhiye. 2023. "Ranking Sub-Watersheds for Flood Hazard Mapping: A Multi-Criteria Decision-Making Approach." Water. 15 (11). https://doi.org/10.3390/w15112128A Novel Attention-Based Model for Semantic Segmentation of Prostate Glands Using Histopathological Images
Inamdar, Mahesh Anil, Raghavendra, U., Gudigar, Anjan, Bhandary, Sarvesh, Salvi, Massimo, Deo, Ravinesh C., Barua, Prabal Datta, Ciaccio, Edward J., Molinari, Filippo and Acharya, RU. Rajendra. 2023. "A Novel Attention-Based Model for Semantic Segmentation of Prostate Glands Using Histopathological Images." IEEE Access. 11, pp. 108982-108994. https://doi.org/10.1109/ACCESS.2023.3321273Efficient daily electricity demand prediction with hybrid deep-learning multi-algorithm approach
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Taherizadeh, Mehrnoosh, Khushemehr, Javid Hojabri, Niknam, Arman, Nguyen-Huy, Thong and MezΕsi, GΓ‘bor. 2023. "Revealing the effect of an industrial flash flood on vegetation area: a case study of Khusheh Mehr in Maragheh-Bonab Plain, Iran." Remote Sensing Applications: Society and Environment. 32. https://doi.org/10.1016/j.rsase.2023.101016Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting
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Tao, Hai, Al-Sulttani, Ahmed H., Salih, Sinan Q., Mohammed, Mustafa K.A., Khan, Mohammad Amir, Beyaztas, Beste Hamiye, Ali, Mumtaz, Elsayed, Salah, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models." Atmospheric Research. 291, pp. 1-13. https://doi.org/https://doi.org/10.1016/j.atmosres.2023.106815The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts?
Loc, Ho Huu, Emadzadeh, Adel, Park, Edward, Nontikansak, Piyanuch and Deo, Ravinesh C.. 2023. "The Great 2011 Thailand flood disaster revisited: Could it have been mitigated by different dam operations based on better weather forecasts? " Environmental Research. 216 (Part 2). https://doi.org/10.1016/j.envres.2022.114493Comparison of machine learning methods emulating process driven crop models
Johnston, David B., Pembleton, Keith G., Huth, Neil I. and Deo, Ravinesh C.. 2023. "Comparison of machine learning methods emulating process driven crop models ." Environmental Modelling and Software. 162. https://doi.org/10.1016/j.envsoft.2023.105634Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm
Jamei, Mehdi, Ali, Mumtaz, Jun, Changhyun, Bateni, Sayed M., Karbasi, Masoud, Farooque, Aitazaz A. and Yaseen, Zaher Mundher. 2023. "Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm." Atmospheric Pollution Research. 14 (6). https://doi.org/10.1016/j.apr.2023.101752Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters
Tao, Hai, Jawad, Ali H., Shather, A.H., Al-Khafaji, Zainab Al, Rashid, Tarik A., Ali, Mumtaz, Al-Ansari, Nadhir Al, Marhoon, Haydar Abdulameer, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters." Environment International. 175, pp. 1-17. https://doi.org/https://doi.org/10.1016/j.envint.2023.107931A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction
Ghimire, Sujan, Nguyen-Huy, Thong, AL-Musaylh, Mohanad S., Deo, Ravinesh, Casillas-Perez, David and Salcedo-sanz, Sancho. 2023. "A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction." Energy. 275, p. 127430. https://doi.org/10.1016/j.energy.2023.127430Climatology and composite evolution of flash drought over Australia and its vegetation impacts
Nguyen, Hanh, Wheeler, Mattew C., Otkin, Jason A., Nguyen-Huy, Thong and Cowan, Timothy. 2023. "Climatology and composite evolution of flash drought over Australia and its vegetation impacts." Journal of Hydrometeorology. 24 (6), p. 1087β1101. https://doi.org/10.1175/JHM-D-22-0033.1Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network
Jamei, Mehdi, Ali, Mumtaz, Karimi, Bakhtiar, Karbasi, Masoud, Farooque, Aitataz Ahsan and Yaseen, Zaher Mundher. 2023. "Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network." Process Safety and Environmental Protection. 174, pp. 115-134. https://doi.org/https://doi.org/10.1016/j.psep.2023.03.062Development of neutrosophic cubic hesitant fuzzy exponential aggregation operators with application in environmental protection problems
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Nguyen-Huy, Thong. 2023. "Digital Farming: An Overview of Its Fundamental Components and Applications." The 4th International Conference of Food Security and Sustainable Agriculture in the Tropics. South Sulawesi, Indonesia 15 - 16 Feb 2023 Indonesia.Modelling future spatial distribution of peanut crops in Australia under climate change scenarios
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Jamei, Mehdi, Karbasi, Masoud, Ali, Mumtaz, Malik, Anurag, Chu, Xuefeng and Yaseen, Zaher Mundher. 2023. "A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm." Expert Systems with Applications. 222. https://doi.org/https://doi.org/10.1016/j.eswa.2023.119811Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images
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Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Karbasi, Masoud, Yaseen, Zaher Mundher and Farooque, Aitazaz Ahsan. 2023. "Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach." Engineering Applications of Artificial Intelligence. 121. https://doi.org/10.1016/j.engappai.2023.105984Designing pentapartitioned neutrosophic cubic set aggregation operator-based air pollution decision-making model
Li, Yi-ming, Khan, Majid, Khurshid, Adnan, Gulistan, Muhammad, Rehman, Ateeq Ur, Ali, Mumtaz, Abdulla, Shahab and Farooque, Aitazaz A.. 2023. "Designing pentapartitioned neutrosophic cubic set aggregation operator-based air pollution decision-making model ." Complex and Intelligent Systems. https://doi.org/10.1007/s40747-023-00971-2Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting
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Sultana, Fazeelat, Gulistan, Muhammad, Ali, Mumtaz, Yaqoob, Naveed, Khan, Muhammad, Rashid, Tabasam and Ahmed, Tauseef. 2023. "A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally ." Journal of Ambient Intelligence and Humanized Computing. 14 (10), p. 13139β13159. https://doi.org/10.1007/s12652-022-03772-6Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression
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Downs, Nathan, Raj, Nawin, Vanos, Jennifer, Parisi, Alfio, Butler, Harry, Deo, Ravinesh, Igoe, Damien, Dexter, Benjamin, Beckman-Downs, Melanie, Turner, Joanna and Dekeyser, Stijn. 2023. "The Playground Shade Index: A New Design Metric for Measuring Shade and Seasonal Ultraviolet Protection Characteristics of Parks and Playgrounds." Photochemistry and Photobiology. 99 (4), pp. 1193-1207. https://doi.org/10.1111/php.13745Using Sequence-to-Sequence Models for Carrier Frequency Offset Estimation of Short Messages and Chaotic Maps
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Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Abdulla, Shahab, Chu, Xuefeng and Yaseen, Zaher Mundher. 2022. "Developing a novel hybrid Auto Encoder Decoder Bidirectional Gated Recurrent Unit model enhanced with empirical wavelet transform and Boruta-Catboost to forecast significant wave height." Journal of Cleaner Production. 379 (Part 2). https://doi.org/10.1016/j.jclepro.2022.134820Modelling and Real-time Optimisation of Air Quality Predictions for Australia through Artificial Intelligence Algorithm
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Jamei, Mehdi, Karimi, Farahnaz, Ali, Mumtaz, Karimi, Bakhtiar, Karbasi, Masoud and Aminpour, Younes. 2022. "Experimental and computational assessment of wetting pattern for two-layered soil profiles in pulse drip irrigation: Designing a novel optimized bidirectional deep learning paradigm." Journal of Hydrology. 614 (Part A), pp. 1-15. https://doi.org/10.1016/j.jhydrol.2022.128496Hybrid Convolutional Neural Network-Multilayer Perceptron Model for Solar Radiation Prediction
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Kath, Jarrod, Craparo, Alessandro, Fong, Youyi, Byrareddy, Vivekananda, Davis, Aaron P., King, Rachel, Nguyen-Huy, Thong, van Asten, Piet J. A., Marcussen, Torben, Mushtaq, Shahbaz, Stone, Roger and Power, Scott. 2022. "Vapour pressure deficit determines critical thresholds for global coffee production under climate change." Nature Food. 3, pp. 871-880. https://doi.org/10.1038/s43016-022-00614-8Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models
Nguyen-Huy, Thong, Deo, Ravinesh C., Khan, Shahjahan, Devi, Aruna, Adeyinka, Adewuyi Ayodele, Apan, Armando A. and Yaseen, Zaher Mundher. 2022. "Student Performance Predictions for Advanced Engineering Mathematics Course With New Multivariate Copula Models." IEEE Access. 10, pp. 45112 -45136. https://doi.org/10.1109/ACCESS.2022.3168322Rapid assessment of mine rehabilitation areas with airborne LiDAR and deep learning: bauxite strip mining in Queensland, Australia
Murray, Xavier, Apan, Armando, Deo, Ravinesh and Maraseni, Tek. 2022. "Rapid assessment of mine rehabilitation areas with airborne LiDAR and deep learning: bauxite strip mining in Queensland, Australia." Geocarto International. 37 (26), pp. 11223-11252. https://doi.org/10.1080/10106049.2022.2048902Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization
Ahmadianfar, Iman, Noori, Ramzia Majeed, Togun, Hussein, Falah, Mayadah W., Homod, Raad Z., Fu, Minglei, Halder, Bijay, Deo, Ravinesh and Yaseen, Zaher Mundher. 2022. "Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization." Knowledge-Based Systems. 250, pp. 1-18. https://doi.org/10.1016/j.knosys.2022.109048Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach
Khosravi, Khabat, Golkarian, Ali, Melesse, Assefa M. and Deo, Ravinesh C.. 2022. "Suspended sediment load modeling using advanced hybrid rotation forest based elastic network approach." Journal of Hydrology. 610, pp. 1-14. https://doi.org/10.1016/j.jhydrol.2022.127963Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study
Halder, Bijay, Bandyopadhyay, Jatisankar, Afan, Haitham Abdulmohsin, Naser, Maryam H., Abed, Salwan Ali, Khedher, Khaled Mohamed, Falih, Khaldoon T., Deo, Ravinesh, Scholz, Miklas and Yaseen, Zaher Mundher. 2022. "Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study." Agronomy. 12 (6), pp. 1-23. https://doi.org/10.3390/agronomy12061268Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Prasad, Ramendra, Li, Jianxin, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction." Scientific Reports. 12 (1), pp. 1-23. https://doi.org/10.1038/s41598-022-09482-5Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network
Deo, Ravinesh C., Grant, Richard H., Webb, Ann, Ghimire, Sujan, Igoe, Damien P., Downs, Nathan J., Al-Musaylh, Mohanad S., Parisi, Alfio V. and Soar, Jeffrey. 2022. "Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network." Stochastic Environmental Research and Risk Assessment. 36, p. 3183β3220. https://doi.org/10.1007/s00477-022-02188-0Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction
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Ghimire, Sujan, Nguyen-Huy, Thong, Deo, Ravinesh C., Casillas-Perez, David and Salcedo-sanz, Sancho. 2022. "Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN-REGST hybrid model." Sustainable Materials and Technologies. 32, pp. 1-24. https://doi.org/10.1016/j.susmat.2022.e00429Hybrid deep CNN-SVR algorithm for solar radiation prediction problems in Queensland, Australia
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Castillo-Boton, C., Casillas-Perez, D., Casanova-Mateo, C., Ghimire, S., Cerro-Prada, E., Gutierrez, P. A., Deo, R. C. and Salcedo-sanz, S.. 2022. "Machine learning regression and classification methods for fog events prediction." Atmospheric Research. 272, pp. 1-23. https://doi.org/10.1016/j.atmosres.2022.106157Quantum Artificial Intelligence Predictions Enhancement by Improving Signal Processing
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Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag, Prasad, Ramendra, Abdulla, Shahab and Yaseen, Zaher Mundher. 2022. "Forecasting Daily Flood Water Level Using Hybrid Advanced Machine Learning Based TimeβVarying Filtered Empirical Mode Decomposition Approach." Water Resources Management. 36 (12), p. 4637β4676. https://doi.org/10.1007/s11269-022-03270-6A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar
Nguyen-Huy, Thong, Kath, Jarrod, Nagler, Thomas, Khaung, Ye, Aung, Thee Su Su, Mushtaq, Shahbaz, Marcussen, Torben and Stone, Roger. 2022. "A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar." Remote Sensing Applications: Society and Environment. 26, pp. 1-19. https://doi.org/10.1016/j.rsase.2022.100733Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction
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Ahmed, Abul Abrar Masrur, Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J., Devi, Aruna, Barua, Prabal D. and Yaseen, Zaher M.. 2022. "Introductory Engineering Mathematics Studentsβ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model." Sustainability. 14 (17), pp. 1-27. https://doi.org/10.3390/su141711070Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors
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Bhagat, Suraj Kumar, Tiyasha, Tiyasha, Kumar, Adarsh, Malik, Tabarak, Jawad, Ali H., Khedher, Khaled Mohamed, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2022. "Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects." Journal of Environmental Management. 309, pp. 1-16. https://doi.org/10.1016/j.jenvman.2022.114711An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis
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Cobon, David, Nguyen-Huy, Thong and Reardon-Smith, Kate. 2019. Drought Outlook Products Review. Toowoomba, Australia. University of Southern Queensland.Study on the Development of Neutrosophic Triplet Ring and Neutrosophic Triplet Field
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Ma, Xiaohong, Feng, Qi, Su, Yonghong, Yu, Tengfei and Deo, Ravinesh C.. 2018. "Characteristics ofΒ ecosystem water use efficiency inΒ aΒ desert riparian forest." Environmental Earth Sciences. 77 (358). https://doi.org/10.1007/s12665-018-7518-zThe influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River
Diop, Lamine, Bodian, Ansoumana, Djaman, Koffi, Yaseen, Zaher Mundher, Deo, Ravinesh C., El-Shafie, Ahmed and Brown, Larry C.. 2018. "The influence of climatic inputs on stream-flow pattern forecasting: case study of Upper Senegal River." Environmental Earth Sciences. 77 (5). https://doi.org/10.1007/s1266Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River
Raheli, Bahare, Aalami, Mohammad Taghi, El-Shafie, Ahmed, Ghorbani, Mohammad Ali and Deo, Ravinesh C.. 2017. "Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River." Environmental Earth Sciences. 76 (14). https://doi.org/10.1007/s12665-017-6842-zMethodology for producing the Drought Monitor
Pudmenzky, Christa, Guillory, Laura, Cobon, David H. and Nguyen-Huy, Thong. 2020. Methodology for producing the Drought Monitor. Toowoomba, Queensland. University of Southern Queensland.Neutrosophic Recommender System for Medical Diagnosis Based on Algebraic Similarity Measure and Clustering
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Thao, Nguyen Xuan, Ali, Mumtaz and Smarandache, Florentin. 2019. "An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis." Journal of Intelligent and Fuzzy Systems. 36 (1), pp. 189-198. https://doi.org/10.3233/JIFS-181084Linguistic Approaches to Interval Complex Neutrosophic Sets in Decision Making
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Cobon, David, Jarvis, Chelsea, Reardon-Smith, Kate, Guillory, Laura, Pudmenzky, Christa, Nguyen-Huy, Thong, Mushtaq, Shahbaz and Stone, Roger. 2021. "Northern Australia Climate Program: supporting adaptation in rangeland grazing systems through more targeted climate forecasts, improved drought information and an innovative extension program." The Rangeland Journal. 43 (3), pp. 87-100. https://doi.org/10.1071/RJ20074Dynamic interval valued neutrosophic set: Modeling decision making in dynamic environments
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Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Feng, Qi, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2022. "New double decomposition deep learning methods for river water level forecasting." Science of the Total Environment. 831, pp. 1-21. https://doi.org/10.1016/j.scitotenv.2022.154722Global disparities in agricultural climate index-based insurance research
Adeyinka, Adewuyi Ayodele, Kath, Jarrod, Nguyen-Huy, Thong, Mushtaq, Shahbaz, Souvignet, Maxime, Range, Matthias and Barratt, Jonathan. 2022. "Global disparities in agricultural climate index-based insurance research." Climate Risk Management. 35, pp. 1-15. https://doi.org/10.1016/j.crm.2022.100394Drought outlook validation using ACCESS-S2 hindcast
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Nguyen-Huy, Thong. 2022. "Systemic risk management in farming - geographic distribution and diversity." Future Drought Fundβs 2022 Science to Practice Forum. 07 - 08 Jun 2022 Australia.Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection
Malik, Anurag, Jamei, Mehdi, Ali, Mumtaz, Prasad, Ramendra, Karbasi, Masoud and Yaseen, Zaher Mundher. 2022. "Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection." Agricultural Water Management. 272. https://doi.org/https://doi.org/10.1016/j.agwat.2022.107812A hierarchical classification/regression algorithm for improving extreme wind speed events prediction
Pelaez-Rodriguez, C., Perez-Aracil, J., Fister, D, Prieto-Godino, L., Deo, R.C. and Salcedo-sanz, S.. 2022. "A hierarchical classification/regression algorithm for improving extreme wind speed events prediction." Renewable Energy. 201 (Part 2), pp. 157-178. https://doi.org/10.1016/j.renene.2022.11.042Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Xiang, Yong, Ahmadianfar, Iman and Yaseen, Zaher Mundher. 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach ." Applied Energy. 326, pp. 1-24. https://doi.org/10.1016/j.apenergy.2022.119925Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag and Yaseen, Zaher Mundher. 2022. "Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer." Computers and Electronics in Agriculture. 198, pp. 1-17. https://doi.org/10.1016/j.compag.2022.107121